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AdaBias: An optimization Method With Bias Correction for Differential Privacy Protection

IEEE ACCESS 2022年 10卷 107010-107021页

作者： Zhao, Xuanyu Hu, Tao Li, Jun Mao, Chunxia Hubei Minzu Univ Coll Intelligent Syst Sci & Engn Enshi 445000 Peoples R China Hubei Engn Res Ctr Selenium Food Nutr & Hlth Inte Enshi 445000 Peoples R China Minist Culture & Tourism Key Lab Performing Art Equipment & Syst Technol Beijing 100007 Peoples R China

A continuous increase in privacy attacks has caused the research and application of differential privacy (DP) to gradually increase. We can improve the efficiency of the DP model by Optimizing its parameters significantly. Inspired by the performance of various optimization methods for differential privacy, this paper proposes an improved RDP-AdaBound optimization method with bias correction, which is called "AdaBias", to increase the performance of Renyi differential privacy (RDP). The bias correction is used to realize the learning rate and speed up the convergence by upper and lower bound functions. We evaluate our method on the three datasets by training two different privacy model. We further compare three traditional optimization algorithms, namely, RDP-SGD, RDP-Adagrad, and RDP-Adam. And we use AdaBias to verify the performance of privacy protection on the COVID-19 dataset. Experimental results show that the new variant better implements learning rate adjustment to accommodate updates of noisy gradients. As a result, it can achieve higher accuracy and lower losses with a lower privacy budget, thereby better protecting data privacy.

关键词： Privacy High-speed networks Adaptation models Differential privacy Deep learning Convergence Heuristic algorithms Differential privacy deep learning optimization algorithm

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Polynomial Attitude Trajectory Planning for Spacecraft with Movable Parts Using Decoupled Strategy

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2024年第1期47卷 72-86页

作者： Fan, Yuqi Xu, Rui Li, Zhaoyu Zhu, Shengying Shang, Haibin Gao, Ai Gao, Yue Beijing Inst Technol Sch Aerosp Engn Beijing 100081 Peoples R China Beijing Inst Technol Key Lab Autonomous Nav & Control Deep Space Explor Beijing 100081 Peoples R China Beijing Inst Technol Key Lab Dynam & Control Flight Vehicle Beijing 100081 Peoples R China Space Star Technol Co Ltd Beijing 100081 Peoples R China

The problem of attitude planning for spacecraft with movable parts under complex pointing constraints is addressed in this paper. To avoid tackling the complex pointing constraints in the high-dimensional system, a novel decoupled strategy is proposed to map the pointing space to the attitude space. Path-planning algorithm Rapidly-exploring Random Tree (RRT)*-Smart is employed in pointing space to generate a collision-free pointing path, and piecewise quintic polynomials are used to represent the attitude path. By proving the differential flatness of spacecraft with movable parts, the inverse dynamics is used to acquire attitude state trajectory in state space. Benefiting from the decoupled strategy, the attitude state trajectory is optimized by a new heuristic time allocation algorithm using binary search with no gradient information needed. The simulation results are discussed, and the performance during each scenario is analyzed.

关键词： Spacecrafts Robot Kinematics Energy Consumption Spacecraft Attitude Control optimization algorithm Satellite Formation Attitude Planning Decoupled Strategy Polynomial Movable Telescope

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Turbulent Airwake Estimation from Helicopter-Ship Wind-Tunnel Data

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JOURNAL OF AIRCRAFT 2024年第4期61卷 1293-1302页

作者： Taymourtash, Neda Quaranta, Giuseppe Polytech Univ Milan Dept Aerosp Sci & Technol I-20156 Milan Italy

This paper presents a stochastic approach for modeling the turbulent airwake suitable for real-time simulation of the helicopter-ship dynamic interface. This approach relies on the measurements of unsteady loads collected during a wind-tunnel test campaign with a scaled helicopter operating over the deck of simple frigate shape 1. Power spectral densities of the measured aerodynamic loads combined with the estimated frequency response functions are used to find, through an optimization algorithm, a model of airwake spectra over the range of frequencies which mainly affects the pilot workload during shipboard operations. Then, a set of autoregressive filters is designed for every particular rotor position and wind-over-deck condition, so that when driven by white noise, the spectrum of the output will reproduce those obtained from the optimization. This approach is applied to three different tested wind directions and three rotor positions by implementing the autoregressive filters into the multibody model of the experimental rotor. Frequency response analysis of the aerodynamic loads demonstrates that the turbulent airwake model obtained from the experimental data can predict the unsteadiness of loads comparable to those measured in the wind tunnel across the bandwidth of interest for pilot activities. The identified airwake models could be applied to a full-scale model to simulate the unsteady loads effectively experienced by the helicopter during a ship landing flight.

关键词： Wind Tunnel Models Helicopter Shipboard Operations Aerodynamic Moments Frequency Response Functions Helicopter Ship Dynamic Interface Acoustic Noise optimization algorithm Flight Testing Computational Fluid Dynamics Multibody Simulation

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Sliding mode control for Markovian jump systems under a switched scheduling protocol

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INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING 2024年第5期38卷 1744-1761页

作者： Zhang, Ying Chen, Bei Shanghai Univ Engn Sci Sch Elect & Elect Engn Shanghai 201620 Peoples R China

This article is concerned with the sliding mode control for Markovian jump systems under transmission constraints. To deal with node congestions, a switched channel scheduling scheme integrating round-robin (RR) protocol and weight try-once-discard (WTOD) protocol is proposed to orchestrate the priority of multiple sensor nodes. At each transmission instant, a system performance-based detector is adopted to select one scheduling protocol between RR and WTOD in a certain event-triggering manner, by which only one sensor node has the priority to access the network. Compared with conventional protocols, the proposed scheduling scheme establishes a dynamic coupling mechanism between channel resource and scheduling rules, aiming to strike a balance between improving system performance and reducing communication resource requirements. Then, a token-dependent sliding mode controller is constructed, and a genetic algorithm-based optimization problem is given to achieve smaller convergent domain. Finally, numerical examples are shown to verify the present control strategy.

关键词： communication scheduling protocol Markovian jump systems optimization algorithm sliding mode control

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Orbital Facility Location Problem for Satellite Constellation Servicing Depots

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JOURNAL OF SPACECRAFT AND ROCKETS 2024年第3期61卷 808-825页

作者： Shimane, Yuri Gollins, Nicholas Ho, Koki Georgia Inst Technol Daniel Guggenheim Sch Aerosp Engn Atlanta GA 30332 USA

This work proposes an adaptation of the facility location problem for the optimal placement of on-orbit servicing depots for satellite constellations in high-altitude orbit. The high-altitude regime, such as medium Earth orbit, is a unique dynamic environment where low-thrust propulsion systems can provide the necessary thrust to conduct plane-change maneuvers between the various orbital planes of the constellation. As such, on-orbit servicing architectures involving servicer spacecraft that conduct roundtrips between servicing depots and the client satellites of the constellation may be conceived. To this end, a new orbital facility location problem formulation is proposed based on binary linear programming, in which the costs of operating and allocating the facility(ies) to satellites are optimized in terms of the sum of the effective mass to low Earth orbit (EMLEO). The low-thrust transfers between the facilities and the clients are computed using a parallel implementation of a Lyapunov feedback controller. The total launch cost of the depot, along with its servicers, propellant, and payload, is taken into account as the cost to establish a given depot. The proposed approach is applied to designing an on-orbit servicing depot architecture for the Galileo and the GPS constellations.

关键词： Robotic Servicing of Geosynchronous Satellites Propellant Space Exploration and Technology optimization algorithm Engineering Economics Facility Location Problem Space Logistics On-Orbit Satellite Servicing

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A new approach of generalized shifted Vieta-Fibonacci polynomials to solve nonlinear variable order time fractional Burgers-Huxley equations

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PHYSICA SCRIPTA 2024年第12期99卷 125258-125258页

作者： Avazzadeh, Zakieh Hassani, Hossein Ebadi, Mohammad Javad Eshkaftaki, Ali Bayati Anhui Univ Stony Brook Inst Hefei 230601 Anhui Peoples R China Univ South Africa Dept Math Sci Florida South Africa Anand Int Coll Engn Dept Math Jaipur 303012 India Chabahar Maritime Univ Dept Math Chabahar Iran Shahrekord Univ Fac Math Shahrekord Iran

In recent years, advancements in optimization techniques and the widespread availability of highperformance computing have made it increasingly feasible to study and develop approximation strategies for nonlinear models. This progress has empowered researchers to address more intricate and realistic challenges associated with these models. This paper introduces the application of a novel polynomial, the generalized shifted Vieta-Fibonacci polynomials ( GSVFPs ) , in solving nonlinear variable order time fractional Burgers-Huxley equations. To mitigate storage and computational costs, new operational matrices ( OMs ) are devised. The proposed algorithm integrates GSVFPs, OMs, and Lagrange multipliers to achieve optimal approximations. Through convergence analysis and numerical examples, the effectiveness and accuracy of the proposed algorithm in solving these equations are demonstrated. The provided numerical illustrations further bolster this assertion.

关键词： generalization of shifted vieta-fibonacci polynomials optimal approximations nonlinears variable order time fractional burgers-huxley equations optimization algorithm lagrange multipliers

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Sparse reconstruction of ultrasonic guided wave signals of fluid-filled pipes by multistrategy hybrid DBO-OMP using dispersive Hanning-windowed chirplet model

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MEASUREMENT 2024年 231卷

作者： Tang, Binghui Wang, Yuemin Gong, Ruqing Zhou, Fan Naval Univ Engn Coll Power Engn Wuhan 430000 Peoples R China

Ultrasonic guided waves (UGWs) in fluid-filled pipes are subject to more severe dispersion and coherent noise than those of vacant pipes, posing significant challenges for defect identification and localization. To this end, a novel sparse signal decomposition method called multistrategy hybrid dung beetle optimization based orthogonal matching pursuit (MHDBO-OMP) using dispersive Hanning-windowed chirplet model was proposed, of which the model not only represents the nonlinear frequency and asymmetric envelope of the dispersive UGW, but also contains the mode and propagation distance information, and this model exhibits better matching and interpretability than the other UGW models. For dispersive perturbed UGW signals with multiple modes and features, MHDBO-OMP achieves high reconstruction accuracy in both signal reconstruction (RES < 0.3) and propagation distance estimation (RES < 3 cm). When applied to experimental UGW signals obtained from water/oil-filled pipes containing cracks and corrosion pits, MHDBO-OMP successfully reconstructs dispersion-compensated signals that solely contain feature signals, and the minimum location error is 0.72 cm while the average location error is 2.65 cm. (c) 2001 Elsevier Science. All rights reserved.

关键词： Ultrasonic guided wave Dispersion optimization algorithm Orthogonal matching pursuit Dispersion compensation

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Performance Analysis and Design of Intelligent Optimising Integral-Based Event-Trigger Control for Autonomous Ground Vehicles Under DoS Attacks

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES

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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2024年第1期9卷 2149-2159页

作者： Cai, Xiao Shi, Kaibo Sun, Yanbin Soh, YengChai Tian, Zhihong Guangzhou Univ Cyberspace Inst Adv Technol Guangzhou 510006 Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore Chengdu Univ Sch Elect Informat & Elect Engn Chengdu 610106 Sichuan Peoples R China Sichuan Univ Coll Elect Engn Chengdu 610065 Sichuan Peoples R China Pazhou Lab Guangzhou 510330 Peoples R China

This study investigates the stability of an autonomous ground vehicle dynamics model in the presence of novel denial of service (DoS) attacks. An algorithm that utilizes an asymmetric Lyapunov-Krasovskii function to reduce decision variables effectively is proposed. By partitioning the LKF for asymmetric LKF trimming, we ensure a tighter upper bound on the remaining part of the function using appropriate integral inequalities. Additionally, an improved alternating direction algorithm (ADA) is employed to optimize the threshold selection problem while considering initial constraints. Subsequently, we design an intelligent integral-based event-triggering controller (IIETC) that incorporates random trigger signal loss to guarantee AGV stability. We conduct a series of experiments utilizing the CarSim-Simulink AGV joint platform. The experimental results serve to validate the effectiveness and superiority of our proposed method.

关键词： Trajectory Security Wheels Vehicle dynamics Stability criteria Tires Sun Cyber attacks autonomous ground vehicle (AGV) Lyapunov-krasovskii function (LKF) event-triggered control optimization algorithm

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Fast Convergence Reliability-Based Design optimization Method Considering Random and Evidence Variables

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AIAA JOURNAL 2022年第4期60卷 2568-2579页

作者： Cid, Clara Baldomir, Aitor Hernandez, Santiago Univ A Coruna Struct Mech Grp Sch Civil Engn Campus Elvina S-N La Coruna 15071 Spain

An efficient approximate reliability-based design optimization method under both aleatory and epistemic uncertainty is presented. As stated by the unified uncertainty analysis based on the first-order reliability method (FORM-UUA), it is possible to merge the probability and evidence theory to quantify the belief and plausibility of a specific performance function under mixed uncertainty. When the number of evidence variables and the number of intervals increase, the number of evaluations grows dramatically. As a result, if the hybrid reliability analysis is included in an optimization problem, usually referred to as nested hybrid reliability-based design optimization (HRBDO), it becomes unmanageable due to its high computational cost. The strategy proposed allows to avoid the computation of the subplausibilities for each focal element as required in the FORM-UUA. This strategy decouples the nested HRBDO into an iterative process with a deterministic optimization and a reliability analysis phase consisting of two separate but connected reliability analyses that handle separately the random and evidence variables. Then, the optimum design obtained is checked and adjusted through the FORM-UUA method. One analytical and one numerical problem are presented to validate the proposed method.

关键词： Probability Distribution Functions Finite Element Modeling Cantilever Beam Young's Modulus Buckling Analysis Aircraft Fuselages Abaqus Monte Carlo Simulation optimization algorithm Search algorithm

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A Novel Approach for Advancing Asphalt Pavement Temperature and Flow Number Predictions Using Optical Microscope algorithm-Least Square Moment Balanced Machine

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JOURNAL OF COMPUTING IN CIVIL ENGINEERING 2024年第6期38卷

作者： Cheng, Min-Yuan Khasani, Riqi Radian Natl Taiwan Univ Sci & Technol Dept Civil & Construct Engn 43Sec 4Keelung Rd Taipei 10607 Taiwan Diponegoro Univ Dept Civil Engn 13 Prof Soedharto Semarang 50275 Indonesia

Asphalt pavement performance is crucial for the sustainable management of road infrastructure. However, achieving accurate predictions remains challenging due to the complex interactions among materials, environmental factors, and traffic loads. In this study, the optical microscope algorithm-least squares moment balanced machine (OMA-LSMBM), an AI-based inference engine, was developed to enhance the accuracy of asphalt performance prediction. This approach integrates machine-learning techniques with optimization algorithms. In the proposed model, LSMBM considers moments to determine the optimal hyperplane, a backpropagation neural network assigns weights to each datapoint, and an OMA optimizes the LSMBM hyperparameters and identifies the optimal feature subset combination. The proposed model was tested using three simulations, i.e., benchmark functions, pavement surface temperature, and asphalt mixture flow number. OMA-LSMBM demonstrated the best function approximation performance, improving the performance metrics and achieving a root mean square error value for pavement temperature prediction that was 6.49%-72.62% less than the comparison models. In terms of predicting flow number, the proposed model showed superior performance over the comparison models with a 11.15%-54.83% lower error rate. These results demonstrate the OMA-LSMBM significantly enhances the accuracy of asphalt performance predictions, which may be directly applied to improving road maintenance strategies and planning activities.

关键词： Asphalt performance Predictive model Moment hyperplane optimization algorithm Feature selection

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